Implant-retained overdenture delivery in 2 visits with a digital workflow.

The conventional method of fabricating implant-retained overdentures involves multiple steps and patient visits. However, the duplication of existing complete dentures could decrease the number of visits and increase patient satisfaction. An existing maxillary implant-retained overdenture was replaced for a 78-year-old man; the existing implant-retained overdenture and his face were scanned at the first visit. The scanned intaglio image was inverted to obtain a virtual maxillary cast and used to fabricate the metal framework of the replacement implant-retained overdenture. Prefabricated artificial teeth were arranged on a 3-dimensional trial denture created from the scan data of the existing implant-retained overdenture. The replacement implant-retained overdenture was fabricated on the metal framework by using the injection molding technique. By using these digital techniques, a stable and esthetic implant-retained overdenture was delivered in 2 visits.

Accurate detection for dental implant and peri-implant tissue by transfer learning of faster R-CNN: a diagnostic accuracy study.

BACKGROUND: The diagnosis of dental implants and the periapical tissues using periapical radiographs is crucial. Recently, artificial intelligence has shown a rapid advancement in the field of radiographic imaging. PURPOSE: This study attempted to detect dental implants and peri-implant tissues by using a deep learning method known as object detection on the implant image of periapical radiographs. METHODS: After implant treatment, the periapical images were collected and data were processed by labeling the dental implant and peri-implant tissue together in the images. Next, 300 images of the periapical radiographs were split into 80:20 ratio (i.e. 80% of the data were used for training the model while 20% were used for testing the model). These were evaluated using an object detection model known as Faster R-CNN, which simultaneously performs classification and localization. This model was evaluated on the classification performance using metrics, including precision, recall, and F1 score. Additionally, in order to assess the localization performance, an evaluation through intersection over union (IoU) was utilized, and, Average Precision (AP) was used to assess both the classification and localization performance. RESULTS: Considering the classification performance, precision = 0.977, recall = 0.992, and F1 score = 0.984 were derived. The indicator of localization was derived as mean IoU = 0.907. On the other hand, considering the indicators of both classification and localization performance, AP showed an object detection level of AP@0.5 = 0.996 and AP@0.75 = 0.967. CONCLUSION: Thus, the implementation of Faster R-CNN model for object detection on 300 periapical radiographic images including dental implants, resulted in high-quality object detection for dental implants and peri-implant tissues.

A detailed description and assessment of outcomes of patients with hospital recorded QTc prolongation.

Corrected QT (QTc) interval prolongation has been shown to be an independent predictor of mortality in many clinical settings and is a common finding in hospitalized patients. The causes and outcomes of patients with extreme QTc interval prolongation during a hospital admission are poorly described. The aim of this study was to prospectively identify patients with automated readings of QTc intervals >550 ms at 1 academic tertiary hospital. One hundred seventy-two patients with dramatic QTc interval prolongation (574 ± 53 ms) were identified (mean age 67.6 ± 15.1 years, 48% women). Most patients had underlying heart disease (60%), predominantly ischemic cardiomyopathy (43%). At lease 1 credible and presumed reversible cause associated with QTc interval prolongation was identified in 98% of patients. The most common culprits were QTc interval-prolonging medications, which were deemed most responsible in 48% of patients, with 25% of these patients taking ≥2 offending drugs. Two patients were diagnosed with congenital long-QT syndrome. Patients with electrocardiograms available before and after hospital admission demonstrated significantly lower preadmission and postdischarge QTc intervals compared with the QTc intervals recorded in the hospital. In conclusion, in-hospital mortality was high in the study population (29%), with only 4% of patients experiencing arrhythmic deaths, all of which were attributed to secondary causes.